The composite leading indicator (CLI) is designed to provide early signals of turning points in business cycles showing fluctuation of the economic activity around its long term potential level. CLIs show short-term economic movements in qualitative rather than quantitative terms.

The series returned is the OECD-harmonised, amplitude-adjusted index at monthly frequency, oscillating around a long-run average of 100: readings above 100 point to above-trend activity ahead and readings below 100 to below-trend activity. Coverage is narrower than the confidence indices – around 22 countries and aggregates.

See definition: https://data.oecd.org/leadind/composite-leading-indicator-cli.htm

Also known as: CLI, leading economic indicator.

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Calculate the Composite Leading Indicator in Python

The Composite Leading Indicator is available in the Economics module of the open-source Finance Toolkit. Install it with:

pip install financetoolkit -U

Then call get_composite_leading_indicator as shown below.

from financetoolkit import Economics

economics = Economics(start_date='2023-06-01', end_date='2023-12-01')

economics.get_composite_leading_indicator(countries=['United States', 'United Kingdom', 'Japan'])

Which returns:

  United States United Kingdom Japan
2023-06 99.1511 99.9353 100.023
2023-07 99.2797 100.196 100.037
2023-08 99.3826 100.419 100.055
2023-09 99.4504 100.622 100.067
2023-10 99.4863 100.806 100.075
2023-11 99.5104 100.998 100.085

Parameters

get_composite_leading_indicator accepts the following parameters:

  • countries (list[str] | str | None, optional): The countries to include in the data. Defaults to None.
  • rolling (int, optional): The rolling window size to use for smoothing the data (simple moving average). Defaults to None.
  • trailing (int, optional): The trailing window size to use for summing the data over trailing periods (e.g. a trailing-4-quarter sum). Defaults to None.
  • growth (bool, optional): Whether to return the growth data or the actual data.
  • lag (int, optional): The number of periods to lag the data by.
  • standardize (bool, optional): Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False.
  • rounding (int | None, optional): The number of decimals to round the results to. Defaults to None.
Consumer Price Index Inflation Rate Consumer Confidence Index Business Confidence Index House Prices Rent Prices Share Prices Exchange Rates Producer Price Index Real Effective Exchange Rate Household Savings Rate Household Debt to Income Ratio

The Economics module page introduces the module, and the sidebar lists all of its functions.

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